Category: hcub2014

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I usually write a series of blog posts I tweet during health IT-related conferences (most recently HFMA, HBMA, MGMA, AMIA, RSNA…). So I really perked my ears when I found out about an important theme at this year’s Healthcare Unbound, the future of healthcare wearable devices and services. I strongly believe that success or failure of wearable technology in healthcare depends on getting “wearable workflow” right!

Below is a list of topics, each with a short description or teaser. I came at wearables in healthcare from a healthcare work improvement perspective. However, as patients more-and-more become members of the care team, the same workflow tech that facilitates care coordination increasingly includes the patient. (See: Patient Experience And Engagement, Workflow And Workflow Tech.)

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One of the questions Vince Kuraitis asked me was, “What are the top 3 barriers to market adoption [of wearable devices and services in healthcare]?”

The most important barriers that came easily and immediately to mind are tiny batteries don’t last long enough, getting personal and professional wearable workflow right is difficult, and the “stigma” of wearing gadgetry, especially on the face.

Wearable “Stigma”

I’ll start with stigma. I had a good friend in medical school who was also getting a PhD in Anthropology. He was studying stigmatized populations. Stigma is a set of negative and often unfair beliefs that a society or group of people have about something, such as race, gender, sexual orientation, obesity, smoking, depression, and, yes, wearables.

The best single example of stigmatization in the wearable space is what happened over time to Google Glass. Setting aside, for the moment, whether Glass is, or is not, the Newton or Segway of wearables, it has become highly stigmatized among everyday gadget consumers. Remarkably, in spite of this stigma, Glass, and similar head-mounted displays continue to attract positive attention in healthcare, particularly for a wide variety of hands-free, remote-viewing, ambient notification-oriented tasks. For example, at the recent wearables in healthcare conference in Indianapolis, 19 of 20 presentations were about Glass. But also telling, at the conference reception, even though many owned Glass, no one wore Glass. (Except me.)

Battery Life

Compared to stigma, the wearable battery life issue is relatively prosaic, but no less an obstacle to widespread adoption in healthcare, particularly among patients. There are wide variety of ongoing institutional clinical trials, many of which maintain multiple sets of wearables, so users can swap a wearable depleted of energy for an wearable that has been charging, swapping and beginning to charge the just depleted wearable, in a wearable charging/user turn taking strategy.

As a result of this obstacle to wearable tech, there’s intense activity in three areas: better batteries, better chargers, and less power hungry microprocessors.

Insufficient and long enough lasting power for wearable devices is even more pernicious than inconvenience for patient, effectively reduce the sell-in-to-able market for wearables, is the a sort of “chilling effect” (by analogy to journalists) on developers. The need to constantly think about how to minimize power requirements limits imagination.

The usually cycle of software development is to assume lots of computer resources, come up with the more kick-ass idea you can, and then optimize. Early versions of Glass (the 1 Gig variety, not the 2 Gig, I have one of each) were particularly prone to heating up and shutting down, not just when shooting video in a consumer use case, but simply when compiling and deploying the Android programs necessary to deliver the apps for users to use.

Wearable Workflow

Finally, we get to my favorite topic: workflow. I’ve even create a character, sort of like Reddy Kilowatt, called Mr. “Wearable Workflow” (shown in the tweet at the beginning of this post). I’ll be talking about “wearable workflow” for the reminder of this blog post series. So, please read my next post What’s The Connection Between Wearable Workflow Platforms and Health IT? if its been published, or tune in a return if you happen on this post just after I published it but before I published the next.

P.S. By the way, you’ll notice that I didn’t address healthcare wearable security. Headlines are full of concerns for notoriously insecure Internet-Of-Things tech. However, as big a (surmountable) obstacle security is, battery life, wearable workflow, and wearable stigma are greater.

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In this case, the answer the question posed by the title of this post is literally about the “connection” between the gadgets we wear on bodies and the data stored in health IT systems. How do we get the right data to or from the right gadget on the right person at the right place and time to the right health IT system. And the answer to this question is: a wearable workflow platform.

I’m sure that “What is a platform?” will be adequate addressed at the Healthcare Unbound conference. But for this post to be self contained I’ll provide this short definition. A platform is an environment (operating system, hardware architecture, set of application programming interfaces) executing a piece of software. An environment does two things. It constrains software development, and it facilitates it. A science fiction fan, I sometimes think of platform as sort of like a holodeck program. Choosing a platform is like running a holodeck program. And once it the platform/holodeck executes, we’ve create a little mini-reality, with its own logic, which we must respect and leverage.

Software platforms have evolved greatly since the sixties. At one time the only platforms were the various hardware architectures. There were no database platforms and operating systems were rudimentary. So, many early software applications basically had to do so much themselves, without help from their environments. These early applications mixed data, user interface, business logic, and, notably for my purposes, workflow together.

The first major transition between software application architectures (made possible by complementary shifts in platform capability) was to take data out of the application and story it in a database. The next major transition moved responsibility for managing elements of the user interface (buttons, dialogue boxes, etc.) out of application into the operating systems. Now, there are lots of different “platforms” out there, natural language platforms, cloud platforms, mobile platforms, etc. But, at the highest level of abstraction we are now seeing the migration of responsibility for representing and managing workflow out of applications into someplace else. Increasingly these workflow platforms reside in the cloud. Increasingly these workflow platforms talk to wearable technology. This is the wearable workflow platform to which I refer.

Suppose you’ve got a laptop, tablet, smartphone, Glass, smartwatch, and smartring (several can vibrate to indicate high priority incoming notifications). Now, imagine all of them “going off” at once! By what means can this be prevented from happening, in a context aware, user customizable, usable user experience sort of way?

There are basically two choices: Orchestration versus choreography. Orchestration is like an orchestra, so there needs to be a conductor. In classic workflow management systems this conductor is a workflow engine. The workflow engine consults a representation of workflow, variously called a workflow or process definition, or sometimes a work plan, and tells everyone what to do. In the past, these models were drawn or constructed in graphical user interfaces. Increasingly these models are learned from actual user behavior.

In our multiple wearable gadget example, whichever device the workflow engine selects, based on a model of work, workflow, or “life flow”, is the device that delivers the notification. And then, if the notification is not acknowledged (perhaps because it’s battery died, or because the device has been temporarily removed), it may escalate.

On the other hand, choreography of wearable devices workflows might be more like dancers or jazz musicians consulting their own limited models of workflow to prevent six devices from buzzing all at once. You could think about this as being a sort of polite conversation, with shared rules of etiquette: “OK if I buzz?”, Might anyone else prefer to buzz instead of me?” “What’s your priority?” “Yes indeed that is higher than mine” “Please go ahead!” But let me know if you’re notification isn’t acknowledged, so I can give it a try!” “Thank you!” “Welcome!” “Think nothing of it!” “Until next time”, “Cheers!”, etc.

I think you can get from the above comparison of wearable workflow the basic idea. Here’s my occasionally tweeted “Mr. “Wearable Workflow” guy! A series of tasks, consuming attention, achieving personal and professional goals, facilitated by wearable technology (personified!). In my next blog posts in this series I’ll drill down into the kinds of process-aware technology we’ll need to be to bring Mr. “Wearable Workflow” to life!

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OK, what Vince actuality asked me was, “What healthcare industry segments or niche markets do you see as particularly promising?” But I’m well known for turning every question about digital health into a question about healthcare workflow and workflow technology. Plus V did indicate he was particularly interested in my experience and view re Google Glass.

I should precede what I’m about to see with a short disclaimer. My answer is extremely influenced by the so-called “availability heuristic” (recency or salience of memory influencing frequency estimate). In spite rejection of Google Glass by the consumer market (see my second post in which I discuss stigma as a barrier to wearable adoption) Glass is still going gang-busters in healthcare, if anything, it’s picking up speed. I recently attended the [wearable conference in Indianapolis] and participated in building a prototype workflow tech-driven Glass app for hospital environmental services.

Plus, since we’re (or at least I’m) talking wearable workflow, not wearables per se, this imposes a lower constraint on the necessary sophistication and complexity of wearable tech and backend systems. And right now, the only almost-to-market wearable of sufficient functionality and real-life playing out prototypes and pilots if Glass.

There may be as many as a hundred Glass in healthcare pilots out there. At the recent wearable in tech conference in Indianapolis, 19 out of 20 presentations were about Glass. Whereas the previous week there’d been two major (not healthcare specific) wearable conferences in which Glass was a small minority of presentations.

Many of the early of Glass startups both inside and outside healthcare are pivoting to smartwatches, which are the most similar to Glass in ability to deliver notifications and accept gesture and voice commands. What’s happening is a generalization of the small form factor, notification, acknowledgement, querying functionality across wearable devices. Of course smartwatches can provide the kind of realtime handsfree video streaming and sharing capability of glass, but the two classes of device not only share a fundamental wearable use case (notifications) but Android Wear and Glass share many parts of the Android platform.

So if Glass and smartwatches are in the lead for delivering sophisticated wearable workflow, where in healthcare will they deliver sophisticated wearable workflow first? Where Google Glass will thrive is a good received wisdom view on this.

“At health systems like San Diego’s Palomar Health and Boston’s Brigham and Women’s and Beth Israel Deaconess and at innovative companies like Pristine, Augmedix, Accenture and Philips, Google Glass is being teased, tossed and turned around to create a platform that allows the healthcare provider to access needed information at the point of care, communicate with colleagues, even create a real-time medical record.”

More generally, the Glass excels at the following three general use cases:

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I’ll not provide a detailed account of how I derived this list. I literally simply asked myself this question, and these are the companies that came to mind. In other words, it is an idiosyncratic list. I will, however, describe my general criteria for why a company interests me, from a wearable workflow perspective.

If you go back to my discussion of orchestrated versus choreographed wearable workflow in What’s The Connection Between Wearable Workflow Platforms and Health IT? you’ll recall the need for either a maestro directing the orchestra or distributed proactive cooperative behavior. In either case, app-to-app behavior is called for. The apps may be on different wearable devices, but it’s still app-to-app behavior. App-to-app behavior has been quite a bugaboo in the mobile health space. Everyone loves their tablet or smartphone, but many hate their EHR. So why not replace EHRs with collections of apps! The problem here is two-fold. First, mobile apps don’t share patient data and context. Second, app-to-app navigation and coordination is, in some ways, even worse than moving from screen-to-screen in a traditional EHR.

Regardless of whether wearable workflow relies on orchestration (workflow engine in the cloud) or choreography (local customizable rule-based interaction) apps on wearable devices will need to communicate, coordinate, etc. So the companies I’m most interested in are those that either have some kind of app-to-app tech, or the kind of sophisticated cloud infrastructure that could participate in a an ecosystem of wearable device to wearable device communication and coordination. Apple is heading down this path with recent iOS upgrades and Continuity. Blackberry has the Flow app-to-app system. Samsung also calls its nascent app-to-app system Flow. Android has had an app-to-app invocation system for some time. It’s likely that wearable device to device workflow tech will evolve out to, or at least leverage this kind of technology.

Then there’s the workflow engine in the cloud approach. Google and Amazon (not listed, maybe next year when they wade more fully into the wearable space) both have cloud-based workflow tech that could be adaptive to orchestrating wearable workflows. Vandrico is a small company in Vancouver, BC, specializing in cross-platform wearable notification management. Their server sits between legacy systems (say hospital EHRs) and wearable devices such as smartwatches. It can format and distribute and accept, in return, acknowledgements and inputs from wearable devices. Salesforce also uses workflow tech, and is bringing cross-platform cloud support to wearables. Jawbone has received enormous private investment, compared to all other wearables. With multiple devices and apps, Jawbone is a natural investigator of wearable healthcare workflow. Finally, Intel, whose chips are to be used in the next version of Glass, already has a partner, Symphony Teleca, working on auto/home automation integration. Wearables are a natural add-one.

Like I said, these are just the companies that pop in to mind, when I ask myself who are the emerging wearable workflow players. I see new potential participants almost every week. It’s really not about the hardware. The hardware are just analogues to desktop widgets. It’s the systems behind the systems that will determine who will dominate wearable tech for the next decade.

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While I’m fascinated by the potential of wearable technology, I’m skeptical about some of the more bombastic growth predictions. We may be pretty close to the top of the famous hype cycle. Plus, I don’t have a crystal ball or time machine. So what I did was an informal meta-analysis. Looked at multiple recent (2013 and 2014) market forecasts, focused on 2018, calculated the average, and divided by half (in the same spirit that engineers calculate safe load limits, then double). I know that these forecasts are about wearables and not the workflow tech I believe will be necessary for workflow tech to achieve some of the higher numbers in the most ambitious forecasts.

Caveats: I went with dollars, not units. Also, I didn’t adjust for current numbers (so don’t address percent growth). I looked for different forecasts from different sources. (You’re welcome to double check this. The first forecast is from BI Intelligence. It’s frequently cited, or at least shown.)

The average market size in in 2018 is $14.2B. Divide by half, to be cautious. 🙂 $7.1B. (Which, by the way, is still greater than the lowest 2018 market estimate.)

Just a word about my dividing by half. Many wearables market forecasts note that since this is a new product category, so there’s no historical context. (Of course, there is prior success and failure of other products in new categories, but how does one quantify, generalize, and extrapolate to this new wearable technology product category.)

Now, what is one to make of my estimate of $7.1B in wearable sales in 2018? Well, you really also need to estimate a Compound Annual Growth Rate (CAGR). Only with both a base and a rate can you estimate the size of the opportunity for new tech and business models to generate profit and return for investors. I’ve seen CAGR numbers between 25% and 75%. So we’re talking a couple billion a year of new revenue. I leave finding five independent estimates and averaging them as an exercise for the reader. (Post it as a comment here, please!).

The next, and last, post in this series is a change of pace. While I don’t address wearable workflow directly, it’s implicit in why I’m interested in what I’m interested in. I’m a Maker. I have Google Glass. I like Intel’s new Edison microprocessor. I’d love to put them together to do cool things. I describe my experience, motivations, and Internet of Things wish list: Google Glass Intel Inside®, The Internet Of Things, and The Maker Movement.

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In this post I discuss the extraordinary Hype Cycle that Google generated, recent news the next version of Glass will use Intel chips, and the Maker Movement. I’ve argued staid health IT needs to become more like the Maker Movement. In order to more fully explain the “personality” of a Maker, I’ve described myself! 🙂 And my efforts to create a “peds-bot,” the 3D printed, microprocessor-animated, Robot-In-My-Pocket.

Are you familiar with Gartner’s Hype Cycle? It starts with a technology trigger. For example, miniaturization, cloud, and head mounted displays (plus other stuff) led to Google Glass.

Exciting potential captures collective imagination and buzz starts to build. The buzz begins to feed on itself. Folks project all kinds of fantastic wishful thinking without really understanding the technology. Of course, even the inventors sometimes don’t completely understand the tech, so this ignorance is a matter of degree. At some point, the hysteria of crowds can no longer sustain its stratospheric flight, and expectations crash. Many are so disappointed they actually think they were sort of hoodwinked. Subconsciously they “punish” the whole idea of the technology, consigning it to the dustbin of tech failures. However, some of the more clear-eyed realists soldier on: Learning, tweaking, improving. Success stores begin to emerge, though begin to be “re-acknowledged” might be the more accurate phrase. Eventually, the new tech is productively integrated into day-to-day workflows and taken for granted. If anyone pauses to reflect about the roller coaster of high hopes and dashed expectations, it’s usually to wonder what the fuss was about.

Glass could be the poster child for The Hype Cycle. It’s Peak of Inflated Expectations was so high, its Trough of Disillusionment so low, the Glass hype cycle is almost a parody of The Hype Cycle, which is already somewhat parody-ish caricature of what happens to new technologies.

I got Glass in June of 2013. At the point it was still climbing toward the Peak of Inflated Expectations. I used it all the time when out and about. No one, and I mean literally no one (unless I was at a tech meetup) knew what it was. Gradually the percent of people in the know increased. I gave personal, two-minute, demos to over 500 people. I never had a bad experience. Then editorializing began, in media and social media, about appearance (dorky), intrusiveness (privacy), and elitism ($1500, never mind it won’t be anywhere near that when it goes retail). While to this day, I’ve never had a bad experience while wearing Glass out and about, I did become increasingly selective about when I wore Glass. I’d never had a bad experience, but I was aware there was some, in my mind, unwarranted animus, and I don’t see any point in blundering into any unpleasant situations. Ah, those halcyon early days, when literally no one knew what Glass was and I felt comfortable wearing Glass without feeling self-conscious.

What’s my point? Well, when the new version of Glass is available next year, small enough to fit into my eyeglasses, I’ll be able to return to those halcyon days. I’ll be able wear Glass without worrying I may be offending someone’s fashion sensibilities. And, since some eyeglasses can cost hundreds of dollars, I don’t think there will be much different between eyeglasses with and eyeglasses without Glass technology.

That leaves privacy. It will remain a potential issue. Glass isn’t actually as privacy-invading, as people imagine. Simple rules of etiquette and good manners will likely suffice. I’ll carry old-fashioned eyeglasses as a backup, if it’s ever a problem. And, eventually, in the long run, social conventions will change, as they always have and aways will.

This blog post is the last in a series about “Wearable Workflow.” I had intended it to be about Google Glass and the Internet of Things. The wearable workflow would have been about workflows among Glass and an increasingly intelligent and proactive world. Coincidently I just received my Edison microprocessor from Intel. Doubly coincidently, the Wall Street Journal just reported that Intel is going to supply chips for future version of Glass.

In the above tweet you can see Glass, the Intel Edison microprocessor, and a corner of a “breakout” board. The breakout board is used for prototyping, because Edison itself is so small. Edison is small so it can be used in wearables. In the lower left corner of the breakout board is a small rectangle and a connector, on to which Edison is mounted in order to communicate with the board. What you can’t see on the Edison, due to the glare, is the tagline, “What Will You Make?” You see, Edison is aimed squarely at the Maker Movement, about which I’ve written previously.

Before I get to the real meat of this post, what I’d like to see happen regarding Glass and Intel, I need to supply some back story. When I got Glass in early 2013, I started looking around for ideas for Glass apps to build in order to better understand how Glass works from an software development point of view.

But what I was really fascinated by was the potential for Glass to interact, to sense and command, my near and distance environments. I’d seen the experience of two elderly bed-ridden relatives and wondered if Glass can be used to control house lights and temperature and such. It can. Here’s I’m talking about using the Glass customizable tilt angle for turning Glass on and off for someone whose head is on a pillow.

And so, above was my path from Glass to the Internet of Things. For example, below I learned how to turn an LED (Light Emitting Diode) on and off over Wi-Fi using Glass. There are gadgets that can accept the LED input and turn on an off an 120 volt appliance.

At that point (and I describe this in order to emphasize the importance of serendipity in the Maker Movement) I began in investigate Bluetooth as an alternative means of communication between Glass and Arduino-compatible microprocessors and modules. I bumped into to nurses from a local children’s hospital and that free wheeling conversion moved from home automation to wearable technology. What if grandma could tell Sparky her pet robot to turn on the lights. The grandkids would like that. Hey, pediatricians would like that. Can you fit Sparky into a shirt pocket? And that is how Mr. RIMP (Robot-In-My-Pocket) was (eventually) born.

Then, at the Wearable & Things conference, where I presented Mr. RIMP, I met Rex St John, Internet of Things Evangelist at Intel. I was aware I needed to make the next version of Mr. RIMP both smaller and more powerful. And that is where the Intel Edison microprocessor comes in. It’s more powerful than the Arduino Uno board version 2.0 of Mr. RIMP uses but also much smaller. And it has the onboard Wi-FI and Bluetooth I need to make Mr. RIMP interact with me and its environment.

While Mr. RIMP is essentially interactive, programmable, toy, it’s also a platform for my exploring my idea of “wearable workflow.” In fact, I have another character, besides Mr. RIMP, I call Mr. “Wearable Workflow,” (inspired by Reddy Kilowatt).

Building Mr. RIMP. Iterating through versions of him. Climbing multiple learning curves at multiple layers of design: software, hardware, 3D “carpentry”, and manufacturability (which I’ve barely begun to investigate). This has been my entree into a fascinating new world of making new things out of almost as new things.

Well those are my thoughts about Google Glass, Intel, and the Maker movement. I told is as a personal story, because I think it’s useful to understand a kind of playful engineering mindset. As Intel, itself, puts it I need “low-cost, product-ready, general purpose compute platforms that help lower the barriers to entry for entrepreneurs of all sizes—from pro makers [CW: that’s me] to consumer electronics and companies working in the Internet of Things (IoT).”

What I need, as an Internet of Things, wearable tech, “inventor,” are components (both hardware and software) that I can easily put together, Lego block-style, and means to control their interactive data and control workflows with each other, their environment, and me. I’m willing to create from scratch whatever I have to, within reason, but at some point either the path of least effort determines what I make, or, if too much effort, then I don’t make.

I need tools, tool chains, infrastructure, platforms, software development kits, example code, best practice documentation, technical support, communities to join (so I can get and give help), and then I need a path to manufacturability (if I want to Mr. RIMP that far).

Now, I know, I’m small potatoes. Basically an advanced hobbyist having fun. However, I think I’m representative of potentially perhaps millions of “Makers.” The confluence of 3D printing, inexpensive but multifunctional microprocessors such as the Intel Edison, wireless cloud, Bluetooth libraries, free resources, documentation, tutorials, and courses on the Web, are returning us, by analogy, to back when tinkerers in garages created entire new industries just having fun exploring the possibilities.

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